Shifts in evolutionary lability underlie independent gains and losses of root-nodule symbiosis in a single clade of plants.

Root nodule symbiosis (RNS) is a complex trait that enables plants to access atmospheric nitrogen converted into usable forms through a mutualistic relationship with soil bacteria. Pinpointing the evolutionary origins of RNS is critical for understanding its genetic basis, but building this evolutionary context is complicated by data limitations and the intermittent presence of RNS in a single clade of ca. 30,000 species of flowering plants, i.e., the nitrogen-fixing clade (NFC). We developed the most extensive de novo phylogeny for the NFC and an RNS trait database to reconstruct the evolution of RNS. Our analysis identifies evolutionary rate heterogeneity associated with a two-step process: An ancestral precursor state transitioned to a more labile state from which RNS was rapidly gained at multiple points in the NFC. We illustrate how a two-step process could explain multiple independent gains and losses of RNS, contrary to recent hypotheses suggesting one gain and numerous losses, and suggest a broader phylogenetic and genetic scope may be required for genome-phenome mapping.

DateLife: leveraging databases and analytical tools to reveal the dated Tree of Life.

Chronograms -phylogenies with branch lengths proportional to time- represent key data on timing of evolutionary events for the study of natural processes in many areas of biological research. Chronograms also provide valuable information that can be used for education, science communication, and conservation policy decisions. Yet, achieving a high-quality reconstruction of a chronogram is a difficult and resource-consuming task. Here we present DateLife, a phylogenetic software implemented as an R package and an R Shiny web application available at www .datelife.org, that provides services for efficient and easy discovery, summary, reuse, and reanalysis of node age data mined from a curated database of expert, peer-reviewed, and openly available chronograms. The main DateLife workflow starts with one or more scientific taxon names provided by a user. Names are processed and standardized to a unified taxonomy, allowing DateLife to run a name match across its local chronogram database that is curated from Open Tree of Life's phylogenetic repository, and extract all chronograms that contain at least two queried taxon names, along with their metadata. Finally, node ages from matching chronograms are mapped using the congruification algorithm to corresponding nodes on a tree topology, either extracted from Open Tree of Life's synthetic phylogeny or one provided by the user. Congruified node ages are used as sec- ondary calibrations to date the chosen topology, with or without initial branch lengths, using different phylogenetic dating methods such as BLADJ, treePL, PATHd8 and MrBayes. We performed a cross-validation test to compare node ages resulting from a DateLife analysis (i.e, phylogenetic dating using secondary calibrations) to those from the original chronograms (i.e, obtained with primary calibrations), and found that DateLife's node age estimates are consistent with the age estimates from the original chronograms, with the largest variation in ages occurring around topologically deeper nodes. Because the results from any software for scientific analysis can only be as good as the data used as input, we highlight the importance of considering the results of a DateLife analysis in the context of the input chronograms. DateLife can help to increase awareness of the existing disparities among alternative hypotheses of dates for the same diversification events, and to support exploration of the effect of alternative chronogram hypotheses on downstream analyses, providing a framework for a more informed interpretation of evolutionary results.

Identifying Climatic Drivers of Hybridization with a New Ancestral Niche Reconstruction Method.

Applications of molecular phylogenetic approaches have uncovered evidence of hybridization across numerous clades of life, yet the environmental factors responsible for driving opportunities for hybridization remain obscure. Verbal models implicating geographic range shifts that brought species together during the Pleistocene have often been invoked, but quantitative tests using paleoclimatic data are needed to validate these models. Here, we produce a phylogeny for Heuchereae, a clade of 15 genera and 83 species in Saxifragaceae, with complete sampling of recognized species, using 277 nuclear loci and nearly complete chloroplast genomes. We then employ an improved framework with a coalescent simulation approach to test and confirm previous hybridization hypotheses and identify one new intergeneric hybridization event. Focusing on the North American distribution of Heuchereae, we introduce and implement a newly developed approach to reconstruct potential past distributions for ancestral lineages across all species in the clade and across a paleoclimatic record extending from the late Pliocene. Time calibration based on both nuclear and chloroplast trees recovers a mid- to late-Pleistocene date for most inferred hybridization events, a timeframe concomitant with repeated geographic range restriction into overlapping refugia. Our results indicate an important role for past episodes of climate change, and the contrasting responses of species with differing ecological strategies, in generating novel patterns of range contact among plant communities and therefore new opportunities for hybridization. The new ancestral niche method flexibly models the shape of niche while incorporating diverse sources of uncertainty and will be an important addition to the current comparative methods toolkit. [Ancestral niche reconstruction; hybridization; paleoclimate; pleistocene.].

A novel method for jointly modeling the evolution of discrete and continuous traits.

The correlated evolution of multiple characters is a crucial aspect of evolutionary change. If change in a particular character influences the evolution of a separate trait, then modeling these features independently can mislead our understanding of the evolutionary process. Progress toward jointly modeling several characters has involved modeling multivariate evolution of the same class of character, but there are far fewer options when jointly modeling traits when one character is discrete and the other is continuous. Here, we develop such a framework to explicitly estimate the joint likelihood for discrete and continuous characters. Specifically, our model combines the probability of observing the continuous character under a generalized OU process with the probability of the discrete character under a hidden Markov model, linked by a shared underlying regime. We use simulation studies to demonstrate that this approach, hOUwie, can accurately evaluate parameter values across a broad set of models. We then apply our model to test whether fleshy and dry fruits of Ericaceae lineages are correlated with their climatic niche evolution as represented by the aridity index. Consistent with expectations, we find that the climatic niche of lineages with fleshy fruits is more conserved while lineages with dry fruits have higher rates of climatic niche evolution and a more humid climatic optimum.

Fossils Do Not Substantially Improve, and May Even Harm, Estimates of Diversification Rate Heterogeneity.

The fossilized birth-death (FBD) model is a naturally appealing way of directly incorporating fossil information when estimating diversification rates. However, an important yet often overlooked property of the original FBD derivation is that it distinguishes between two types of sampled lineages. Here, we first discuss and demonstrate the impact of severely undersampling, and even not including fossils that represent samples of lineages that also had sampled descendants. We then explore the benefits of including fossils, generally, by implementing and then testing two types of FBD models, including one that converts a fossil set into stratigraphic ranges, in more complex likelihood-based models that assume multiple rate classes across the tree. Under various simulation scenarios, including a scenario that exists far outside the set of models we evaluated, including fossils rarely outperform analyses that exclude them altogether. At best, the inclusion of fossils improves precision but does not influence bias. Similarly, we found that converting the fossil set to stratigraphic ranges, which is one way to remedy the effects of undercounting the number of k-type fossils, results in turnover rates and extinction fraction estimates that are generally underestimated. Although fossils remain essential for understanding diversification through time, in the specific case of understanding diversification given an existing, largely modern tree, they are not especially beneficial. [Fossilized birth-death; fossils; MiSSE; state speciation extinction; stratigraphic ranges; turnover rate.].

A flexible method for estimating tip diversification rates across a range of speciation and extinction scenarios.

Estimates of diversification rates at the tips of a phylogeny provide a flexible approach for correlation analyses with multiple traits and to map diversification rates in space while also avoiding the uncertainty of deep time rate reconstructions. Available methods for tip rate estimation make different assumptions, and thus their accuracy usually depends on the characteristics of the underlying model generating the tree. Here, we introduce MiSSE, a trait-free, state-dependent speciation and extinction approach that can be used to estimate varying speciation, extinction, net diversification, turnover, and extinction fractions at the tips of the tree. We compare the accuracy of tip rates inferred by MiSSE against similar methods and demonstrate that, due to certain characteristics of the model, the error is generally low across a broad range of speciation and extinction scenarios. MiSSE can be used alongside regular phylogenetic comparative methods in trait-related diversification hypotheses, and we also describe a simple correction to avoid pseudoreplication from sister tips in analyses of independent contrasts. Finally, we demonstrate the capabilities of MiSSE, with a renewed focus on classic comparative methods, to examine the correlation between plant height and turnover rates in eucalypts, a species-rich lineage of flowering plants.

Retiring "Cradles" and "Museums" of Biodiversity.

In 1974, G. Ledyard Stebbins provided a metaphor illustrating how spatial gradients of biodiversity observed today are by-products of the way environment-population interactions drive species diversification through time. We revisit the narrative behind Stebbins's "cradles" and "museums" of biodiversity to debate two points. First, the usual high-speciation versus low-extinction and tropical versus temperate dichotomies are oversimplifications of the original metaphor and may obscure how gradients of diversity are formed. Second, the way in which we use modern gradients of biodiversity to interpret the potential historical processes that generated them are often still biased by the reasons that motivated Stebbins to propose his original metaphor. Specifically, the field has not yet abandoned the idea that species-rich areas and "basal lineages" indicate centers of origin, nor has it fully appreciated the role of traits as regulators of environment-population dynamics. We acknowledge that the terms "cradles" and "museums" are popular in the literature and that terminologies can evolve with the requirements of the field. However, we also argue that the concepts of cradles and museums have outlived their utility in studies of biogeography and macroevolution and should be replaced by discussions of actual processes at play.

A Spatially Explicit Model of Stabilizing Selection for Improving Phylogenetic Inference.

Ultraconserved elements (UCEs) are stretches of hundreds of nucleotides with highly conserved cores flanked by variable regions. Although the selective forces responsible for the preservation of UCEs are unknown, they are nonetheless believed to contain phylogenetically meaningful information from deep to shallow divergence events. Phylogenetic applications of UCEs assume the same degree of rate heterogeneity applies across the entire locus, including variable flanking regions. We present a Wright-Fisher model of selection on nucleotides (SelON) which includes the effects of mutation, drift, and spatially varying, stabilizing selection for an optimal nucleotide sequence. The SelON model assumes the strength of stabilizing selection follows a position-dependent Gaussian function whose exact shape can vary between UCEs. We evaluate SelON by comparing its performance to a simpler and spatially invariant GTR+Γ model using an empirical data set of 400 vertebrate UCEs used to determine the phylogenetic position of turtles. We observe much improvement in model fit of SelON over the GTR+Γ model, and support for turtles as sister to lepidosaurs. Overall, the UCE-specific parameters SelON estimates provide a compact way of quantifying the strength and variation in selection within and across UCEs. SelON can also be extended to include more realistic mapping functions between sequence and stabilizing selection as well as allow for greater levels of rate heterogeneity. By more explicitly modeling the nature of selection on UCEs, SelON and similar approaches can be used to better understand the biological mechanisms responsible for their preservation across highly divergent taxa and long evolutionary time scales.

The evolution of a tropical biodiversity hotspot.

The tropics are the source of most biodiversity yet inadequate sampling obscures answers to fundamental questions about how this diversity evolves. We leveraged samples assembled over decades of fieldwork to study diversification of the largest tropical bird radiation, the suboscine passerines. Our phylogeny, estimated using data from 2389 genomic regions in 1940 individuals of 1283 species, reveals that peak suboscine species diversity in the Neotropics is not associated with high recent speciation rates but rather with the gradual accumulation of species over time. Paradoxically, the highest speciation rates are in lineages from regions with low species diversity, which are generally cold, dry, unstable environments. Our results reveal a model in which species are forming faster in environmental extremes but have accumulated in moderate environments to form tropical biodiversity hotspots.

The ecological and genomic basis of explosive adaptive radiation.

Speciation rates vary considerably among lineages, and our understanding of what drives the rapid succession of speciation events within young adaptive radiations remains incomplete1-11. The cichlid fish family provides a notable example of such variation, with many slowly speciating lineages as well as several exceptionally large and rapid radiations12. Here, by reconstructing a large phylogeny of all currently described cichlid species, we show that explosive speciation is solely concentrated in species flocks of several large young lakes. Increases in the speciation rate are associated with the absence of top predators; however, this does not sufficiently explain explosive speciation. Across lake radiations, we observe a positive relationship between the speciation rate and enrichment of large insertion or deletion polymorphisms. Assembly of 100 cichlid genomes within the most rapidly speciating cichlid radiation, which is found in Lake Victoria, reveals exceptional 'genomic potential'-hundreds of ancient haplotypes bear insertion or deletion polymorphisms, many of which are associated with specific ecologies and shared with ecologically similar species from other older radiations elsewhere in Africa. Network analysis reveals fundamentally non-treelike evolution through recombining old haplotypes, and the origins of ecological guilds are concentrated early in the radiation. Our results suggest that the combination of ecological opportunity, sexual selection and exceptional genomic potential is the key to understanding explosive adaptive radiation.

Unlocking a signal of introgression from codons in Lachancea kluyveri using a mutation-selection model.

BACKGROUND: For decades, codon usage has been used as a measure of adaptation for translational efficiency and translation accuracy of a gene's coding sequence. These patterns of codon usage reflect both the selective and mutational environment in which the coding sequences evolved. Over this same period, gene transfer between lineages has become widely recognized as an important biological phenomenon. Nevertheless, most studies of codon usage implicitly assume that all genes within a genome evolved under the same selective and mutational environment, an assumption violated when introgression occurs. In order to better understand the effects of introgression on codon usage patterns and vice versa, we examine the patterns of codon usage in Lachancea kluyveri, a yeast which has experienced a large introgression. We quantify the effects of mutation bias and selection for translation efficiency on the codon usage pattern of the endogenous and introgressed exogenous genes using a Bayesian mixture model, ROC SEMPPR, which is built on mechanistic assumptions about protein synthesis and grounded in population genetics. RESULTS: We find substantial differences in codon usage between the endogenous and exogenous genes, and show that these differences can be largely attributed to differences in mutation bias favoring A/T ending codons in the endogenous genes while favoring C/G ending codons in the exogenous genes. Recognizing the two different signatures of mutation bias and selection improves our ability to predict protein synthesis rate by 42% and allowed us to accurately assess the decaying signal of endogenous codon mutation and preferences. In addition, using our estimates of mutation bias and selection, we identify Eremothecium gossypii as the closest relative to the exogenous genes, providing an alternative hypothesis about the origin of the exogenous genes, estimate that the introgression occurred ∼6×108 generation ago, and estimate its historic and current selection against mismatched codon usage. CONCLUSIONS: Our work illustrates how mechanistic, population genetic models like ROC SEMPPR can separate the effects of mutation and selection on codon usage and provide quantitative estimates from sequence data.

Leaf reflectance spectra capture the evolutionary history of seed plants.

Leaf reflectance spectra have been increasingly used to assess plant diversity. However, we do not yet understand how spectra vary across the tree of life or how the evolution of leaf traits affects the differentiation of spectra among species and lineages. Here we describe a framework that integrates spectra with phylogenies and apply it to a global dataset of over 16 000 leaf-level spectra (400-2400 nm) for 544 seed plant species. We test for phylogenetic signal in spectra, evaluate their ability to classify lineages, and characterize their evolutionary dynamics. We show that phylogenetic signal is present in leaf spectra but that the spectral regions most strongly associated with the phylogeny vary among lineages. Despite among-lineage heterogeneity, broad plant groups, orders, and families can be identified from reflectance spectra. Evolutionary models also reveal that different spectral regions evolve at different rates and under different constraint levels, mirroring the evolution of their underlying traits. Leaf spectra capture the phylogenetic history of seed plants and the evolutionary dynamics of leaf chemistry and structure. Consequently, spectra have the potential to provide breakthrough assessments of leaf evolution and plant phylogenetic diversity at global scales.

Gene expression of functionally-related genes coevolves across fungal species: detecting coevolution of gene expression using phylogenetic comparative methods.

BACKGROUND: Researchers often measure changes in gene expression across conditions to better understand the shared functional roles and regulatory mechanisms of different genes. Analogous to this is comparing gene expression across species, which can improve our understanding of the evolutionary processes shaping the evolution of both individual genes and functional pathways. One area of interest is determining genes showing signals of coevolution, which can also indicate potential functional similarity, analogous to co-expression analysis often performed across conditions for a single species. However, as with any trait, comparing gene expression across species can be confounded by the non-independence of species due to shared ancestry, making standard hypothesis testing inappropriate. RESULTS: We compared RNA-Seq data across 18 fungal species using a multivariate Brownian Motion phylogenetic comparative method (PCM), which allowed us to quantify coevolution between protein pairs while directly accounting for the shared ancestry of the species. Our work indicates proteins which physically-interact show stronger signals of coevolution than randomly-generated pairs. Interactions with stronger empirical and computational evidence also showing stronger signals of coevolution. We examined the effects of number of protein interactions and gene expression levels on coevolution, finding both factors are overall poor predictors of the strength of coevolution between a protein pair. Simulations further demonstrate the potential issues of analyzing gene expression coevolution without accounting for shared ancestry in a standard hypothesis testing framework. Furthermore, our simulations indicate the use of a randomly-generated null distribution as a means of determining statistical significance for detecting coevolving genes with phylogenetically-uncorrected correlations, as has previously been done, is less accurate than PCMs, although is a significant improvement over standard hypothesis testing. These methods are further improved by using a phylogenetically-corrected correlation metric. CONCLUSIONS: Our work highlights potential benefits of using PCMs to detect gene expression coevolution from high-throughput omics scale data. This framework can be built upon to investigate other evolutionary hypotheses, such as changes in transcription regulatory mechanisms across species.

Phylotastic: Improving Access to Tree-of-Life Knowledge With Flexible, on-the-Fly Delivery of Trees.

A comprehensive phylogeny of species, i.e., a tree of life, has potential uses in a variety of contexts, including research, education, and public policy. Yet, accessing the tree of life typically requires special knowledge, complex software, or long periods of training. The Phylotastic project aims make it as easy to get a phylogeny of species as it is to get driving directions from mapping software. In prior work, we presented a design for an open system to validate and manage taxon names, find phylogeny resources, extract subtrees matching a user's taxon list, scale trees to time, and integrate related resources such as species images. Here, we report the implementation of a set of tools that together represent a robust, accessible system for on-the-fly delivery of phylogenetic knowledge. This set of tools includes a web portal to execute several customizable workflows to obtain species phylogenies (scaled by geologic time and decorated with thumbnail images); more than 30 underlying web services (accessible via a common registry); and code toolkits in R and Python (allowing others to develop custom applications using Phylotastic services). The Phylotastic system, accessible via http://www.phylotastic.org, provides a unique resource to access the current state of phylogenetic knowledge, useful for a variety of cases in which a tree extracted quickly from online resources (as distinct from a tree custom-made from character data) is sufficient, as it is for many casual uses of trees identified here.

On the Matrix Condition of Phylogenetic Tree.

Phylogenetic comparative analyses use trees of evolutionary relationships between species to understand their evolution and ecology. A phylogenetic tree of n taxa can be algebraically transformed into an n by n squared symmetric phylogenetic covariance matrix C where each element c ij in C represents the affinity between extant species i and extant species j. This matrix C is used internally in several comparative methods: for example, it is often inverted to compute the likelihood of the data under a model. However, if the matrix is ill-conditioned (ie, if κ , defined by the ratio of the maximum eigenvalue of C to the minimum eigenvalue of C , is too high), this inversion may not be stable, and thus neither will be the calculation of the likelihood or parameter estimates that are based on optimizing the likelihood. We investigate this potential issue and propose several methods to attempt to remedy this issue.

Reef fish functional traits evolve fastest at trophic extremes.

Trophic ecology is thought to exert a profound influence on biodiversity, but the specifics of the process are rarely examined at large spatial and evolutionary scales. We investigate how trophic position and diet breadth influence functional trait evolution in one of the most species-rich and complex vertebrate assemblages, coral reef fishes, within a large-scale phylogenetic framework. We show that, in contrast with established theory, functional traits evolve fastest in trophic specialists with narrow diet breadths at both very low and high trophic positions. Top trophic level specialists exhibit the most functional diversity, while omnivorous taxa with intermediate trophic positions and wide diet breadth have the least functional diversity. Our results reveal the importance of trophic position in shaping evolutionary dynamics while simultaneously highlighting the incredible trophic and functional diversity present in coral reef fish assemblages.

Population Genetics Based Phylogenetics Under Stabilizing Selection for an Optimal Amino Acid Sequence: A Nested Modeling Approach.

We present a new phylogenetic approach, selection on amino acids and codons (SelAC), whose substitution rates are based on a nested model linking protein expression to population genetics. Unlike simpler codon models that assume a single substitution matrix for all sites, our model more realistically represents the evolution of protein-coding DNA under the assumption of consistent, stabilizing selection using a cost-benefit approach. This cost-benefit approach allows us to generate a set of 20 optimal amino acid-specific matrix families using just a handful of parameters and naturally links the strength of stabilizing selection to protein synthesis levels, which we can estimate. Using a yeast data set of 100 orthologs for 6 taxa, we find SelAC fits the data much better than popular models by 104-105 Akike information criterion units adjusted for small sample bias. Our results also indicated that nested, mechanistic models better predict observed data patterns highlighting the improvement in biological realism in amino acid sequence evolution that our model provides. Additional parameters estimated by SelAC indicate that a large amount of nonphylogenetic, but biologically meaningful, information can be inferred from existing data. For example, SelAC prediction of gene-specific protein synthesis rates correlates well with both empirical (r=0.33-0.48) and other theoretical predictions (r=0.45-0.64) for multiple yeast species. SelAC also provides estimates of the optimal amino acid at each site. Finally, because SelAC is a nested approach based on clearly stated biological assumptions, future modifications, such as including shifts in the optimal amino acid sequence within or across lineages, are possible.

Hidden state models improve state-dependent diversification approaches, including biogeographical models.

The state-dependent speciation and extinction (SSE) models have recently been criticized due to their high rates of "false positive" results. Many researchers have advocated avoiding SSE models in favor of other "nonparametric" or "semiparametric" approaches. The hidden Markov modeling (HMM) approach provides a partial solution to the issues of model adequacy detected with SSE models. The inclusion of "hidden states" can account for rate heterogeneity observed in empirical phylogenies and allows for reliable detection of state-dependent diversification or diversification shifts independent of the trait of interest. However, the adoption of HMM has been hampered by the interpretational challenges of what exactly a "hidden state" represents, which we clarify herein. We show that HMMs in combination with a model-averaging approach naturally account for hidden traits when examining the meaningful impact of a suspected "driver" of diversification. We also extend the HMM to the geographic state-dependent speciation and extinction (GeoSSE) model. We test the efficacy of our "GeoHiSSE" extension with both simulations and an empirical dataset. On the whole, we show that hidden states are a general framework that can distinguish heterogeneous effects of diversification attributed to a focal character.

AnnotationBustR: an R package to extract subsequences from GenBank annotations.

BACKGROUND: DNA sequences are pivotal for a wide array of research in biology. Large sequence databases, like GenBank, provide an amazing resource to utilize DNA sequences for large scale analyses. However, many sequence records on GenBank contain more than one gene or are portions of genomes. Inconsistencies in the way genes are annotated and the numerous synonyms a single gene may be listed under provide major challenges for extracting large numbers of subsequences for comparative analysis across taxa. At present, there is no easy way to extract portions from many GenBank accessions based on annotations where gene names may vary extensively. RESULTS: The R package AnnotationBustR allows users to extract sequences based on GenBank annotations through the ACNUC retrieval system given search terms of gene synonyms and accession numbers. AnnotationBustR extracts subsequences of interest and then writes them to a FASTA file for users to employ in their research endeavors. CONCLUSION: FASTA files of extracted subsequences and accession tables generated by AnnotationBustR allow users to quickly find and extract subsequences from GenBank accessions. These sequences can then be incorporated in various analyses, like the construction of phylogenies to test a wide range of ecological and evolutionary hypotheses.